Rachel Thomas (academic)

thumb|Rachel_Thomas_at_Linux_Foundation Rachel Thomas (academic) is an American computer scientist and founding Director of the Center for Applied Data Ethics at the University of San Francisco. Together with Jeremy Howard, she is co-founder of fast.ai. Quotes Deep learning refers to a specific class of algorithm that are also known as “multi-layered neural networks.” These algorithms are getting amazing, world-class results on a variety of problems. For example, identifying what object is in a picture, translating text, or understanding speech. It’s used in voice recognition as well. I don’t think of these people as traditional mentors, but I’ve learned a lot from them and have been encouraged by them. One is my co-founder Jeremy Howard. I’ve learned a ton working with him in how he solves problems both technically in coding and in business. It’s the problem I’m working on with fast.ai: making deep learning easier to use and getting it into the hands of people that wouldn’t normally have access. One of our students that just finished our course is a Canadian dairy farmer. He said he needed to learn how to use AI to improve the health of his goats’ udders. I thought that was such an awesome application and something I never would have thought of! I want every dairy farmer and people no matter their profession or where they are in the world to be able to use this technology on the problems that they care about. Medicine is definitely a huge one. It’s important to remember that there is a global shortage of doctors that is quite large in some countries. For instance, in Nigeria, it would take 300 years to train enough doctors to fill the shortage with their existing pipeline. I know a pediatric radiologist from South Africa who said there are only 14 pediatric radiologists for the entire African continent. My hope is that deep learning will help doctors and community health workers be more effective. Rachel Thomas explains what Deep Learning is and their progress at Fast.ai External links Category:Computer scientists from the United States Category:Women academics from the United States Category:Entrepreneurs Category:Living people